Investigation of the Kinetics of Carbonation Reaction with Cao-Based Sorbents Using Experiments and Aspen Plus Simulation
Bibliographic record
Abstract
The intrinsic kinetics of the carbonation reactions for two limestones (Havelock and Cadomin) were studied using an atmospheric thermogravimetric analyzer (ATGA) and a pressurized thermogravimetric analyzer (PTGA). A grain model was applied to measure the kinetic parameters. The order of the carbonation reaction was related to the carbon dioxide (CO2) partial pressure, changing from the first order to the zero order when the CO2 partial pressure exceeded ~0.7 atm for both limestones. The rate of carbonation reaction increased with increasing temperature up to 675°C and decreased with further increases. No significant effect of particle size was found on the rate of carbonation reaction. Thermodynamic and kinetic simulations of the carbonation reaction using the Aspen Plus simulator was performed, obtaining the optimal temperature of 650°C. The activation energies were 32.1 and 20.3 kJ/mol for the tested Havelock and Cadomin limestones, respectively. The simulation results from the kinetic model were in good agreement with the experimental data, showing the reversible characteristic of the carbonation reaction. The shift in the mechanism of the carbonation reaction with temperature and the shift in the reaction order with CO2 partial pressure were demonstrated by both the experiments and simulation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".